Matthijs J. H. M. van der Loos

Most Reported Genetic Associations With General Intelligence Are Probably False Positives

General intelligence (g) and virtually all other behavioral traits are heritable. Associations between g and specific single-nucleotide polymorphisms (SNPs) in several candidate genes involved in brain function have been reported. We sought to replicate published associations between g and 12 specific genetic variants (in the genes DTNBP1, CTSD, DRD2, ANKK1, CHRM2, SSADH, COMT, BDNF, CHRNA4, DISC1, APOE, and SNAP25) using data sets from three independent, well-characterized longitudinal studies with samples of 5,571, 1,759, and 2,441 individuals. Of 32 independent tests across all three data sets, only 1 was nominally significant. By contrast, power analyses showed that we should have expected 10 to 15 significant associations, given reasonable assumptions for genotype effect sizes. For positive controls, we confirmed accepted genetic associations for Alzheimer’s disease and body mass index, and we used SNP-based calculations of genetic relatedness to replicate previous estimates that about half of the variance in g is accounted for by common genetic variation among individuals. We conclude that the molecular genetics of psychology and social science requires approaches that go beyond the examination of candidate genes.

The Molecular Genetic Architecture of Self-Employment

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg 2/σP 2 = 25%, h 2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.

Genome-wide association studies and the genetics of entrepreneurship

We are currently investigating genetic influences on self-employment in an international research consortium using genome-wide association studies (GWAS). By meta-analysing results from numerous independent samples we address identification issues arising from multiple testing. To our knowledge, this is the earliest attempt to apply GWAS to an economic outcome of a relatively general nature. Our study will reveal potentials and limitations of this approach for economic research.

Serum testosterone levels in males are not associated with entrepreneurial behavior in two independent observational studies

Previous research has suggested a positive association between testosterone (T) and entrepreneurial behavior in males. However, this evidence was found in a study with a small sample size and has not been replicated. In the present study, we aimed to verify this association using two large, independent, population-based samples of males. We tested the association of T with entrepreneurial behavior, operationalized as self-employment, using data from the Rotterdam Study (N=587) and the Study of Health in Pomerania (N=1697). Total testosterone (TT) and sex hormone-binding globulin (SHBG) were measured in the serum. Free testosterone (FT), non-SHBG-bound T (non-SHBG-T), and the TT/SHBG ratio were calculated and used as measures of bioactive serum T, in addition to TT adjusted for SHBG. Using logistic regression models, we found no significant associations between any of the serum T measures and self-employment in either of the samples. To our knowledge, this is the first large-scale study on the relationship between serum T and entrepreneurial behavior.

Including item characteristics in the probabilistic latent semantic analysis model for collaborative filtering

We propose a new hybrid recommender system that combines some advantages of collaborative and content-based recommender systems. While it uses ratings data of all users, as do collaborative recommender systems, it is also able to recommend new items and provide an explanation of its recommendations, as do content-based systems. Our approach is based on the idea that there are communities of users that find the same characteristics important to like or dislike a product. This model is an extension of the probabilistic latent semantic model for collaborative filtering with ideas based on clusterwise linear regression. On a movie data set, we show that the model is competitive to other recommenders and can be used to explain the recommendations to the users.

A Genome-Wide Association Study of Educational Attainment

Twin and adoption studies have consistently found that genetic variation is an important source of heterogeneity in economic outcomes such as educational attainment and income. The advent of inexpensive, genome-wide scans is now making it increasingly feasible to directly examine specific genetic variants that predict individual differences. In this paper, we conduct a genome-wide association study (GWAS) of educational achievement. In the first stage, we used data on over 360,000 genetic markers throughout the genome from the Framingham Heart Study, a family-based sample of nearly 8,500 individuals, and found a number of markers with suggestive associations with educational attainment. The most promising variants were significant at the 5⋅10⁻⁷ level. In the second stage, we attempted to replicate the most significant first-stage associations using data from the Rotterdam study, an independent sample of over 9,500 individuals. None of the first-stage associations replicated, suggesting that the first-stage results were false positives. We discuss the challenges that arise when doing inference in genoeconomics research, emphasizing the importance of properly correcting for multiple hypothesis testing and of replicating significant results in independent samples. We also discuss issues of power and sample size. We argue that if proper attention is given to these methodological challenges, the burgeoning field of genoeconomics will add a valuable new dimension to our understanding of heterogeneity in economic outcomes.

Functional characterization of the PCLO p.Ser4814Ala variant associated with major depressive disorder reveals cellular but not behavioral differences

Genome-wide association studies have suggested a role for a genetic variation in the presynaptic gene PCLO in major depressive disorder (MDD). As with many complex traits, the PCLO variant has a small contribution to the overall heritability and the association does not always replicate. One variant (rs2522833, p.Ser4814Ala) is of particular interest given that it is a common, nonsynonymous exon variant near a calcium-sensing part of PCLO. It has been suggested that the molecular effects of such variations penetrate to a variable extent in the population due to phenotypic and genotypic heterogeneity at the population level. More robust effects may be exposed by studying such variations in isolation, in a more homogeneous context. We tested this idea by modeling PCLO variation in a mouse knock-in model expressing the Pclo(SA)(/)(SA) variant. In the highly homogeneous background of inbred mice, two functional effects of the SA-variation were observed at the cellular level: increased synaptic Piccolo levels, and 30% increased excitatory synaptic transmission in cultured neurons. Other aspects of Piccolo function were unaltered: calcium-dependent phospholipid binding, synapse formation in vitro, and synaptic accumulation of synaptic vesicles. Moreover, anxiety, cognition and depressive-like behavior were normal in Pclo(SA)(/)(SA) mice. We conclude that the PCLO p.Ser4814Ala missense variant produces mild cellular phenotypes, which do not translate into behavioral phenotypes. We propose a model explaining how (subtle) cellular phenotypes do not penetrate to the mouse behavioral level but, due to genetic and phenotypic heterogeneity and non-linearity, can produce association signals in human population studies.